Senior Software Engineer, Planning and Control Integration – Autonomous Vehicles

Overview

• NVIDIA has continuously reinvented itself over two decades.
• Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing.
• More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.
• The NVIDIA China Autonomous Driving Team is looking for a hands-on software engineer to shape how vehicles plan, decide, and act on the road.
• In this role, you will own the driving behavior of our autonomous driving stack across multiple production programs — performing deep root-cause analysis, adapting planning and control algorithms to diverse vehicle platforms, and building automation tools that scale our engineering impact globally.
• You will ride in test vehicles, tune real-world performance, and collaborate directly with OEM partners to deliver safe, comfortable, and production-ready autonomous driving behavior.
• What you’ll be doing: Own end-to-end Planning & Control integration across the NVIDIA AV software stack, including module interfaces, data flow, timing, and cross-team integration and validation with perception, localization, and vehicle actuation systems Design, develop, and optimize planning and control algorithms for core L2, L2+, and L2++ driving scenarios, and drive their integration into the production software stack Perform system integration, carline adaptation, and parameter tuning for planning and control modules across different vehicle platforms - adapting to diverse vehicle dynamics, steering systems, braking characteristics, sensor configurations, and OEM platform requirements Build and maintain cross-carline integration validation workflows and comparison tooling to systematically evaluate integration behavior differences across vehicle platforms and accelerate multi-carline integration at scale Improve the safety, comfort, feasibility, smoothness, and system-level robustness of the integrated planning and control system across different road geometries, traffic conditions, and vehicle platforms Analyze, triage, and resolve cross-module Planning & Control integration and functional issues across multiple autonomous driving programs from L2 through L4 Perform integration root-cause analysis, bring-up validation, and performance tuning using simulation, replay tools, vehicle logs, on-vehicle diagnostics, and real-world testing, and provide clear resolution proposals Collaborate with global teams and OEM partners to drive software integration, validation, release readiness, and production delivery; travel domestically and internationally for on-vehicle integration testing and customer collaboration as needed What we need to see: BS/MS in Computer Science, Electrical Engineering, Robotics, Vehicle Engineering, or a related field 5+ years of autonomous driving, ADAS, or robotics software development experience, with strong C++ and Python skills Solid knowledge of motion planning, trajectory planning, vehicle control, vehicle dynamics/kinematics, or numerical optimization Hands-on experience integrating planning and control modules into a production or prototype autonomous driving software stack Experience with multi-carline adaptation, on-vehicle debugging, parameter tuning, simulation, log analysis, and production software development Strong analytical, problem-solving, and English communication skills Proficient English communication skills (written and verbal) — able to produce clear technical reports and participate in meetings with global teams Ways to stand out from the crowd: Production experience developing and integrating planning and control algorithms for autonomous driving or ADAS systems Multi-carline development experience - adapting and tuning planning and control parameters across different vehicle dynamics, steering systems, and brake characteristics Experience driving end-to-end Planning & Control integration across modules, vehicle platforms, or OEM programs, handling complex interactive scenarios such as lane changes, merging, yielding, cut-ins, and intersections, has knowledge of functional safety or autonomous driving validation standards Expertise in path/speed planning, trajectory optimization, model predictive control, or constrained numerical optimization Experience building developer tools, test automation frameworks, or cross-carline comparison workflows.